Multi-objective optimisation on motorized momentum exchange tether for payload orbital transfer

Chen, Y. and Cartmell, M.P. (2007) Multi-objective optimisation on motorized momentum exchange tether for payload orbital transfer. In: Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2007, Singapore, 25-28 September 2007. IEEE Computer Society: Piscataway, N.J., USA, pp. 987-993. ISBN 9781424413393 (doi:10.1109/CEC.2007.4424577)

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Abstract

The symmetrical motorised momentum exchange tether, is intended to be excited by a continuous torque, so that, it can be applied as an orbital transfer system. The motor drive accelerates the tether, and increases the relative velocity of payloads fitted to each end. In order to access better tether performance, a higher efficiency index needs to be achieved. Meanwhile, the stress in each tether sub-span should stay within the stress limitations. The multi-objective optimisation methods of Genetic Algorithms can be applied for tether performance enhancement. The tether's efficiency index and stress are used as multi-objectives, and the analysis of the resulting Pareto front suggests a set of solutions for the parameters of the motorised momentum exchange tether when used for payload transfer, in order to achieve relative high transfer performance, and safe tether strength.

Item Type:Book Sections
Additional Information:©2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting / republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Cartmell, Prof Matthew and Chen, Mr Yi
Authors: Chen, Y., and Cartmell, M.P.
Subjects:T Technology > TJ Mechanical engineering and machinery
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
Publisher:IEEE Computer Society
ISBN:9781424413393
Copyright Holders:Copyright © 2007 IEEE Computer Society
First Published:First published in Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2007, Singapore, 25-28 September 2007
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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